Recently, attention has been paid to individual identification/authentication systems that make use of biometrical features of individuals such as faces, voices, fingerprints, and iris patterns. Among them, face recognition is considered the most natural and most effective method for identifying an individual because it is like what a human being does and it does not require use of particular facilities. In the face recognition, extraction of features of an individual face is a key for construction of a more effective system. Although many feature extraction techniques have been proposed, these techniques are fairly complicated and therefore it is difficult to apply them to real-time face recognition.
Recently, there has been proposed a very simple and highly reliable face recognition method on the basis of a vector quantization (VQ) algorithm (see Non-Patent Document 1 below).
Similar data recognition devices are disclosed also in Patent Document 1 and Patent Document 2 below.
Non-Patent Document 1:
K. Kotani, C. Qiu, and T. Ohmi, “Face Recognition Using Vector Quantization Histogram Method”, Proc. 2002 Int. Conf. on Image Processing, Vol. II of III, pp. II-105-II-108, 2002
Patent Document 1:
Japanese Unexamined Patent Application Publication (JP-A) No. 2000-101437
Patent Document 2:
Japanese Unexamined Patent Application Publication (JP-A) No. 2002-203241
In the foregoing face recognition method, a histogram generated from usage frequency of each of code vectors obtained by VQ processing of a face image is used as a very effective individual feature extraction technique. By applying proper filtering and VQ processing to a face image, it is possible to extract useful features for face recognition. The result of a test using the AT&T face database showed a recognition rate of 95.6%. When a 1.1 GHz personal computer is used, a processing time for one image is 194 msec. The VQ histogram method is much simpler and faster than previous face recognition methods but is still not sufficient for application to high-speed data recognition such as video rate (standard video is 30 frames per second and the video rate represents an image recognition speed of about 33 msec corresponding to one frame) recognition.